Why AI databases are becoming so huge – a look at vector stores

What actually happens behind the scenes when an AI searches thousands of documents for the right answer? Whether it's ChatGPT, RAG applications, or semantic search, so-called vector stores are working in the background. You rarely see them, but nothing works without them: they play a decisive role in determining the quality and performance of AI systems. The problem is that these databases can become really large. And really expensive.

In this episode, we take a look at what's inside a vector store and how it works.